■ Abstract Apoptosis is a genetically programmed, morphologically distinct form of cell death that can be triggered by a variety of physiological and pathological stimuli. Studies performed over the past 10 years have demonstrated that proteases play critical roles in initiation and execution of this process. The caspases, a family of cysteine-dependent aspartate-directed proteases, are prominent among the death proteases. Caspases are synthesized as relatively inactive zymogens that become activated by scaffold-mediated transactivation or by cleavage via upstream proteases in an intracellular cascade. Regulation of caspase activation and activity occurs at several different levels: ( a) Zymogen gene transcription is regulated; ( b) antiapoptotic members of the Bcl-2 family and other cellular polypeptides block proximity-induced activation of certain procaspases; and ( c) certain cellular inhibitor of apoptosis proteins (cIAPs) can bind to and inhibit active caspases. Once activated, caspases cleave a variety of intracellular polypeptides, including major structural elements of the cytoplasm and nucleus, components of the DNA repair machinery, and a number of protein kinases. Collectively, these scissions disrupt survival pathways and disassemble important architectural components of the cell, contributing to the stereotypic morphological and biochemical changes that characterize apoptotic cell death.

Mammalian caspases: structure ,a ctivation ,s ubstrates, and functions during apoptosis

Currently, new technologies have enabled the design of smart applications that are used as decision-making tools in the problems of daily life. The key issue in designing such an application is the increasing level of user interaction. Mixed reality (MR) is an emerging technology that deals with maximum user interaction in the real world compared to other similar technologies. Developing an MR application is complicated, and depends on the different components that have been addressed in previous literature. In addition to the extraction of such components, a comprehensive study that presents a generic framework comprising all components required to develop MR applications needs to be performed. This review studies intensive research to obtain a comprehensive framework for MR applications. The suggested framework comprises five layers: the first layer considers system components; the second and third layers focus on architectural issues for component integration; the fourth layer is the application layer that executes the architecture; and the fifth layer is the user interface layer that enables user interaction. The merits of this study are as follows: this review can act as a proper resource for MR basic concepts, and it introduces MR development steps and analytical models, a simulation toolkit, system types, and architecture types, in addition to practical issues for stakeholders such as considering MR different domains.

A Review on Mixed Reality: Current Trends, Challenges and Prospects

Mobile devices with passive depth sensing capabilities are ubiquitous, and recently active depth sensors have become available on some tablets and AR/VR devices. Although real-time depth data is accessible, its rich value to mainstream AR applications has been sorely under-explored. Adoption of depth-based UX has been impeded by the complexity of performing even simple operations with raw depth data, such as detecting intersections or constructing meshes. In this paper, we introduce DepthLab, a software library that encapsulates a variety of depth-based UI/UX paradigms, including geometry-aware rendering (occlusion, shadows), surface interaction behaviors (physics-based collisions, avatar path planning), and visual effects (relighting, 3D-anchored focus and aperture effects). We break down the usage of depth into localized depth, surface depth, and dense depth, and describe our real-time algorithms for interaction and rendering tasks. We present the design process, system, and components of DepthLab to streamline and centralize the development of interactive depth features. We have open-sourced our software at https://github.com/googlesamples/arcore-depth-lab to external developers, conducted performance evaluation, and discussed how DepthLab can accelerate the workflow of mobile AR designers and developers. With DepthLab we aim to help mobile developers to effortlessly integrate depth into their AR experiences and amplify the expression of their creative vision.

https://dl.acm.org/doi/pdf/10.1145/3379337.3415881

DepthLab: Real-time 3D Interaction with Depth Maps for Mobile Augmented Reality

Various studies have widely utilized mixed reality (MR) in primary and secondary (K-12) education. Nevertheless, there has been relatively no explicit focus on a substantial amount of studies that are reviewed systematically in order to present and suggest the educational benefits of MR technology for the development of learning environments. The present systematic literature review describes the current state of knowledge and practices using MR in K-12 education and provides guidance for educators and scholars focusing on instructional design contexts by critically appraising and summarizing the existing research. It also outlines a wide range of results yielded by quantitative, qualitative and mixed-method studies to investigate potential benefits, difficulties, and effectiveness of MR environments across various learning subjects. Overall, 21 studies published from 2002 until 2018 in 18 international peer-reviewed journals were analysed, with 11 and 10 studies regarding primary and secondary education, respectively. This review informs educators and scholars about insights and evidence gained by prior findings on the current state-of-the-art research so that provide a contribution of scientific knowledge and innovation using MR environments in different learning subjects. Implications for practice and research are discussed in detail, as MR has the potential to influence students’ engagement, participation, skill acquisition, and embodied learning experience for knowledge transfer within well-structured instructional design contexts.

A systematic literature review of mixed reality environments in K-12 education

Writing or sketching on whiteboards is an essential part of collaborative discussions in business meetings, reading groups, design sessions, and interviews. However, prior work in collaborative virtual reality (VR) systems has rarely explored the design space of multi-user layouts and interaction modes with virtual whiteboards. In this paper, we present CollaboVR, a reconfigurable framework for both co-located and geographically dispersed multi-user communication in VR. Our system unleashes users’ creativity by sharing freehand drawings, converting 2D sketches into 3D models, and generating procedural animations in real-time. To minimize the computational expense for VR clients, we leverage a cloud architecture in which the computational expensive application (Chalktalk) is hosted directly on the servers, with results being simultaneously streamed to clients. We have explored three custom layouts – integrated, mirrored, and projective – to reduce visual clutter, increase eye contact, or adapt different use cases. To evaluate CollaboVR, we conducted a within-subject user study with 12 participants. Our findings reveal that users appreciate the custom configurations and real-time interactions provided by CollaboVR. We have open sourced CollaboVR at https://github.com/snowymo/CollaboVR to facilitate future research and development of natural user interfaces and real-time collaborative systems in virtual and augmented reality.

CollaboVR: A Reconfigurable Framework for Creative Collaboration in Virtual Reality

Social media in virtual reality is in a high-growth market segment with influential products and services in virtual tourism, remote education, and business meetings. Nevertheless, previous systems have never achieved an online platform which renders a 6DoF mirrored world with geotagged social media in real time. In this paper, we introduce the technical detail behind Geollery.com which reconstructs a mirrored world at two levels of detail. Given a pair of latitude and longitude coordinates, our pipeline streams and caches depth maps, street view panoramas, and building polygons from Google Maps and OpenStreetMap APIs. At a fine level of detail for close-up views, we render textured meshes using adjacent local street views and depth maps. When viewed from afar, we apply projection mappings to 3D geometries extruded from building polygons for a coarse level of detail. In contrast to teleportation, our system allows users to virtually walk through the mirrored world at the street level. Our system integrates geotagged social media from both internal users and external sources such as Twitter, Yelp, and Flicker. We validate our real-time strategies of Geollery.com on various platforms including mobile phones, workstations, and head-mounted displays.

https://dl.acm.org/doi/pdf/10.1145/3329714.3338126

Project Geollery.com: Reconstructing A Live Mirrored World With Geotagged Social Media

Advanced AR/VR headsets often have a dedicated depth sensor or multiple cameras, high processing power, and a high-capacity battery to track hands or controllers. However, these approaches are not compatible with the small form factor and limited thermal capacity of lightweight AR devices. In this paper, we present RetroSphere, a self-contained 6 degree of freedom (6DoF) controller tracker that can be integrated with almost any device. RetroSphere tracks a passive controller with just 3 retroreflective spheres using a stereo pair of mass-produced infrared blob trackers, each with its own infrared LED emitters. As the sphere is completely passive, no electronics or recharging is required. Each object tracking camera provides a tiny Arduino-compatible ESP32 microcontroller with the 2D position of the spheres. A lightweight stereo depth estimation algorithm that runs on the ESP32 performs 6DoF tracking of the passive controller. Also, RetroSphere provides an auto-calibration procedure to calibrate the stereo IR tracker setup. Our work builds upon Johnny Lee’s Wii remote hacks and aims to enable a community of researchers, designers, and makers to use 3D input in their projects with affordable off-the-shelf components. RetroSphere achieves a tracking accuracy of about 96.5% with errors as low as ∼ 3.5 cm over a 100 cm tracking range, validated with ground truth 3D data obtained using a LIDAR camera while consuming around 400 mW. We provide implementation details, evaluate the accuracy of our system, and demonstrate example applications, such as mobile AR drawing, 3D measurement, etc. with our Retrosphere-enabled AR glass prototype.

RetroSphere: Self-Contained Passive 3D Controller Tracking for Augmented Reality

Advanced AR/VR headsets often have a dedicated depth sensor or multiple cameras, high processing power, and a high-capacity battery to track hands or controllers. However, these approaches are not compatible with the small form factor and limited thermal capacity of lightweight AR devices. In this paper, we present RetroSphere, a self-contained 6 degree of freedom (6DoF) controller tracker that can be integrated with almost any device. RetroSphere tracks a passive controller with just 3 retroreflective spheres using a stereo pair of mass-produced infrared blob trackers, each with its own infrared LED emitters. As the sphere is completely passive, no electronics or recharging is required. Each object tracking camera provides a tiny Arduino-compatible ESP32 microcontroller with the 2D position of the spheres. A lightweight stereo depth estimation algorithm that runs on the ESP32 performs 6DoF tracking of the passive controller. Also, RetroSphere provides an auto-calibration procedure to calibrate the stereo IR tracker setup. Our work builds upon Johnny Lee's Wii remote hacks and aims to enable a community of researchers, designers, and makers to use 3D input in their projects with affordable off-the-shelf components. RetroSphere achieves a tracking accuracy of about 96.5% with errors as low as ~3.5 cm over a 100 cm tracking range, validated with ground truth 3D data obtained using a LIDAR camera while consuming around 400 mW. We provide implementation details, evaluate the accuracy of our system, and demonstrate example applications, such as mobile AR drawing, 3D measurement, etc. with our Retrosphere-enabled AR glass prototype.

RetroSphere

Reconstruction of the physical world in real time has been a grand challenge in computer graphics and 3D vision. In this paper, we introduce an interactive pipeline to reconstruct a mirrored world at two levels of detail. Given a pair of latitude and longitude coordinates, our pipeline streams and caches depth maps, street view panoramas, and building polygons from Google Maps and OpenStreetMap APIs. At a fine level of detail for close-up views, we render textured meshes using adjacent local street views and depth maps. When viewed from afar, we apply projection mappings to 3D geometries extruded from building polygons for a coarse level of detail. In contrast to teleportation, our system allows users to virtually walk through the mirrored world at the street level. We present an application of our approach by incorporating it into a mixed-reality social platform, Geollery, and validate our real-time strategies on various platforms including mobile phones, workstations, and head-mounted displays.

Interactive Fusion of 360° Images for a Mirrored World

Neural representations have shown great promise in their ability to represent radiance and light fields while being very compact compared to the image set representation. However, current representations are not well suited for streaming as decoding can only be done at a single level of detail and requires downloading the entire neural network model. Furthermore, high-resolution light field networks can exhibit flickering and aliasing as neural networks are sampled without appropriate filtering. To resolve these issues, we present a progressive multi-scale light field network that encodes a light field with multiple levels of detail. Lower levels of detail are encoded using fewer neural network weights enabling progressive streaming and reducing rendering time. Our progressive multi-scale light field network addresses aliasing by encoding smaller anti-aliased representations at its lower levels of detail. Additionally, per-pixel level of detail enables our representation to support dithered transitions and foveated rendering.

Progressive Multi-Scale Light Field Networks

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